Spatially Offset Raman Spectroscopy (SORS) is a technique for interrogating subsurface composition of turbid
samples noninvasively. This study generically addresses a fundamental question relevant to a wide range of SORS studies,
which is, how deep SORS probes for any specific spatial offset when analyzing a turbid sample. Or in turn, ...
Spatially Offset Raman Spectroscopy (SORS) is a technique for interrogating subsurface composition of turbid
samples noninvasively. This study generically addresses a fundamental question relevant to a wide range of SORS studies,
which is, how deep SORS probes for any specific spatial offset when analyzing a turbid sample. Or in turn, what magnitude
of spatial offset one should select to probe a specific depth. This issue is addressed by using Monte Carlo simulations, under
the assumption of negligible absorption, which establishes that the key parameter governing the extent of the probed zone
for a point-like illumination and point-like collection SORS geometry is the reduced scattering coefficient of the medium.
This can either be deduced from literature data or directly estimated from a SORS measurement by evaluating the Raman
intensity profile from multiple spatial offsets. Once this is known, the extent of the probed zone can be determined for any
specific SORS spatial offset using the Monte Carlo simulation results presented here. The proposed method was tested
using experimental data on stratified samples by analyzing the signal detected from a thin layer moved through a stack of
layers using both non-absorbing and absorbing samples. The proposed simple methodology provides important additional
information on SORS measurements with direct relevance to a wide range of SORS applications including biomedical,
pharmaceutical, security, forensics, and cultural heritage.